Embrace a new level of integration and insight for proactive, ‘big picture’ asset performance improvements. Learn how these scalable digital solutions can help you reduce footprint, increase throughput, and maximize uptime, by combining evergreen data, physics-driven models, and AI.
Pipeline integrity
Integrated AI drives predictive data-driven solutions for pipeline monitoring, inspection, and modeling to prevent leaks, failures, or incidents that can compromise throughput, safety, and the environment
Overview
Avoid costly downtime and environmental damage, and safeguard your license to operate. Using data across a range of formats, operators can now manage the integrity of their pipeline assets using the latest in AI/machine learning (ML) models to determine if conditions have been met for repair.
Value is delivered through:
- Contextualized workflows, from fit-for-purpose solutions, to reduce false alarm rates.
- Prioritization and decision recommendations reduced from weeks/months to minutes.
- System agnosticism—any data/model can be integrated.
- Intuitive risk indexing for proactive asset management.
Solutions can incorporate your current methodology, analysis, criteria setting, and more into the application for consistency and reliability in the analysis.
The operations data foundation layer can integrate and contextualize any data type or set, regardless of OEM. Inspection data in any digitized format can be uploaded for immediate analysis, with automated data alignment and criteria mapping through AI/ML techniques.
Intelligent pipeline integrity management
Digital services for production performance
Proactively minimize risks to pipeline integrity and mitigate threats to operations by acquiring actionable insights via real-time monitoring, domain expertise, and AI-based analytics.
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